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AT A GLANCE

It’s becoming even more of an urgent priority for organizations to tap into artificial intelligence (AI) to assist in hiring, managing, and optimizing contingent workers.

Adoption remains in the early stages as per a survey published by the Harvard Business Review, with only 20% reporting use one or more AI technology at scale or in a core part of their business.

While AI is a broad topic with far-reaching implications for organizations and business processes, there are some areas that stand out when it comes to contingent workforce management (CWM).

August 01, 2018

Impactful Intelligence: AI and CWM

As we’ve discussed in a separate article in this quarter’s edition of DCR TrendLine, the labor market is tight, with the number of openings eclipsing the number of available job seekers. As such, it becomes even more critical for organizations to source and hire the right skilled candidate. However, a recent statistic reveals that 74% of employers claim they’ve hired the wrong person for a position, costing businesses an average of nearly $15,000 on every bad hire.

In such a landscape, it’s becoming even more of an urgent priority for organizations to tap into artificial intelligence (AI) to assist in hiring, managing, and optimizing contingent workers. Countless studies have shown that machine learning and predictive analytics offer exciting possibilities towards increasing efficiency, reducing operational costs, improving talent quality, and growing revenue. And corporate executives understand that with nearly three in four considering AI to be a business advantage that is fundamental to their future operation, according to a recent report by PwC. However, adoption remains in the early stages as per a survey published by the Harvard Business Review, with only 20% reporting use one or more AI technology at scale or in a core part of their business.

AI, Innovation in Contingent Workforce Management

While AI is a broad topic with far-reaching implications for organizations and business processes, there are some areas that stand out when it comes to contingent workforce management (CWM).

One of a vendor management system’s (VMS) key functions is helping hiring managers find the best candidates to fill job openings. AI can help take this matching to the next level by using machine learning to predict job performance for specific roles. Using AI in such a manner could potentially enable hiring managers to make more insightful decisions that would decrease time to fill, maximize talent and reduce cost.

The best VMS platforms offer guidance software aimed at making users’ workflows easier, simpler, and more efficient. The next generation in this area is embedded intelligence powered by AI, or a form of a virtual assistant that can help users with tasks through the contingent workforce management life cycle. Businesses processes could be combined with company policies and managerial preferences and built into the system to help the virtual assistant provide more relevant suggestions, driving user engagement and delivering a better customer experience.

The increased integration of AI into existing technologies can open a realm of opportunities for companies. By analyzing data sets and performing automated work in the background, AI promises to deliver faster decision-making, freeing up valuable resources for stakeholders. Combined with human expertise, the augmented intelligence driven by AI could help organizations drive cost savings, increase talent quality, and improve the effectiveness of their contingent workforce programs.